And in 30 years it will be another 30 years away.
LLMs are so incredibly useful and powerful but they will NEVER be AGI. I actually wonder if the success of (and subsequent obsession with) LLMs is putting true AGI further out of reach. All that these AI companies see are the $$$. When the biggest "AI Research Labs" like OpenAI shifted to product-izing their LLM offerings I think the writing was on the wall that they don't actually care about finding AGI.
Got it. So this is now a competition between...
1. Fusion power plants 2. AGI 3. Quantum computers 4. Commercially viable cultured meat
May the best "imminent" fantasy tech win!
Of those 4 I expect commercial cultured meat far sooner than the rest.
People over-estimate the short term and under-estimate the long term.
Compound growth starting from 0 is... always 0. Current LLMs have 0 general reasoning ability
We haven't even taken the first step towards AGI
WTF, my calculator is high school was already a step towards AGI.
0 and 0.0001 may be difficult to distinguish.
You need to show evidence of that 0.0001 first otherwise you're going off blind faith
I didn't make a claim either way.
LLMs may well reach a closed endpoint without getting to AGI - this is my personal current belief - but people are certainly motivated to work on AGI
Oh for sure. I'm just fighting against the AGI hype. If we survive another 10,000 years I think we'll get there eventually but it's anyone's guess as to when
People overestimate outcomes and underestimate timeframes
People will keep improving LLMs, and by the time they are AGI (less than 30 years), you will say, "Well, these are no longer LLMs."
Will LLMs approach something that appears to be AGI? Maybe. Probably. They're already "better" than humans in many use cases.
LLMs/GPTs are essentially "just" statistical models. At this point the argument becomes more about philosophy than science. What is "intelligence?"
If an LLM can do something truly novel with no human prompting, with no directive other than something it has created for itself - then I guess we can call that intelligence.
How many people do you know who are capable of doing something truly novel? Definitely not me, I'm just an average phd doing average research.
Literally every single person I know that is capable of holding a pen or typing on a keyboard can create something new.
Something new != truly novel. ChatGPT creates something new every time I ask it a question.
adjective: novel
definition: new or unusual in an interesting way.
ChatGPT can create new things, sure, but it does so at your directive. It doesn't do that because it wants to which gets back to the other part of my answer.
When an LLM can create something without human prompting or directive, then we can call that intelligence.
What does intelligence have to do with having desires or goals? An amoeba can do stuff on its own but it's not intelligent. I can imagine a god-like intelligence that is a billion times smarter and more capable than any human in every way, and it could just sit idle forever without any motivation to do anything.
Does the amoeba does make choices?
Do you make that choice? Did I?
I did a really fun experiment the other night. You should try it.
I was a little bored of the novel I have been reading so I sat down with Gemini and we collaboratively wrote a terrible novel together.
At the start I was promoting it a lot about the characters and the plot, but eventually it starting writing longer and longer chapters by itself. Characters were being killed off left right and center.
It was hilariously bad, but it was creative and it was fun.
I'm a lowly high school diploma holder. I thought the point of getting a PhD meant you had done something novel (your thesis).
Is that wrong?
My phd thesis, just like 99% of other phd theses, does not have any “truly novel” ideas.
Just because it's something that no one has done yet, doesn't mean that it's not the obvious-to-everyone next step in a long, slow march.
AI manufacturers aren't comparing their models against most people; they now say its "smarter than 99% of people" or "performs tasks at a PhD level".
Look, your argument ultimately reduces down to goalpost-moving what "novel" means, and you can position those goalposts anywhere you want depending on whether you want to push a pro-AI or anti-AI narrative. Is writing a paragraph that no one has ever written before "truly novel"? I can do that. AI can do that. Is inventing a new atomic element "truly novel"? I can't do that. Humans have done that. AI can't do that. See?
Isn't the human brain also "just" a big statistical model as far as we know? (very loosely speaking)
What the hell is general intelligence anyway? People seem to think it means human-like intelligence, but I can't imagine we have any good reason to believe that our kinds of intelligence constitute all possible kinds of intelligence--which, from the words, must be what "general" intelligence means.
It seems like even if it's possible to achieve GI, artificial or otherwise, you'd never be able to know for sure that thats what you've done. It's not exactly "useful benchmark" material.
> What the hell is general intelligence anyway?
OpenAI used to define it as "a highly autonomous system that outperforms humans at most economically valuable work."
Now they used a Level 1-5 scale: https://briansolis.com/2024/08/ainsights-openai-defines-five...
So we can say AGI is "AI that can do the work of Organizations":
> These “Organizations” can manage and execute all functions of a business, surpassing traditional human-based operations in terms of efficiency and productivity. This stage represents the pinnacle of AI development, where AI can autonomously run complex organizational structures.
There's nothing general about AI-as-CEO.
That's the opposite of generality. It may well be the opposite of intelligence.
An intelligent system/individual reliably and efficiently produces competent, desirable, novel outcomes in some domain, avoiding failures that are incompetent, non-novel, and self-harming.
Traditional computing is very good at this for a tiny range of problems. You get efficient, very fast, accurate, repeatable automation for a certain small set of operation types. You don't get invention or novelty.
AGI will scale this reliably across all domains - business, law, politics, the arts, philosophy, economics, all kinds of engineering, human relationships. And others. With novelty.
LLMs are clearly a long way from this. They're unreliable, they're not good at novelty, and a lot of what they do isn't desirable.
They're barely in sight of human levels of achievement - not a high bar.
The current state of LLMs tells us more about how little we expect from human intelligence than about what AGI could be capable of.
Apparently OpenAI now just defines it monetarily as "when we can make $100 billion from it." [0]
[0] https://gizmodo.com/leaked-documents-show-openai-has-a-very-...
That's what "economically valuable work" means.
The way some people confidently assert that we will never create AGI, I am convinced the term essentially means "machine with a soul" to them. It reeks of religiosity.
I guess if we exclude those, then it just means the computer is really good at doing the kind of things which humans do by thinking. Or maybe it's when the computer is better at it than humans and merely being as good as the average human isn't enough (implying that average humans don't have natural general intelligence? Seems weird.)
When we say "the kind of things which humans do by thinking", we should really consider that in the long arc of history. We've bootstrapped ourselves from figuring out that flint is sharp when it breaks, to being able to do all of the things we do today. There was no external help, no pre-existing dataset trained into our brains, we just observed, experimented, learned and communicated.
That's general intelligence - the ability to explore a system you know nothing about (in our case, physics, chemistry and biology) and then interrogate and exploit it for your own purposes.
LLMs are an incredible human invention, but they aren't anything like what we are. They are born as the most knowledgeable things ever, but they die no smarter.
>you'd never be able to know for sure that thats what you've done.
Words mean what they're defined to mean. Talking about "general intelligence" without a clear definition is just woo, muddy thinking that achieves nothing. A fundamental tenet of the scientific method is that only testable claims are meaningful claims.
Looking back at CUDA, deep learning, and now LLM hypes, I would bet it'll be cycles of giant groundbreaking leaps followed by giant complete stagnations, rather than LLM improving 3% per year for coming 30 years.
They‘ll get cheaper and less hardware demanding but the quality improvements get smaller and smaller, sometimes hardly noticeable outside benchmarks
What was the point of this comment? It's confrontational and doesn't add anything to the conversation. If you disagree, you could have just said that, or not commented at all.
There's been a complaint for several decades that "AI can never succeed" - because when, say, expert systems are developed from AI research, and they become capable of doing useful things, then the nay-sayer say "That's not AI, that's just expert systems".
This is somewhat defensible, because what the non-AI-researcher means by AI - which may be AGI - is something more than expert systems by themselves can deliver. It is possible that "real AI" will be the combination of multiple approaches, but so far all the reductionist approaches (that expert systems, say, are all that it takes to be an AI) have proven to be inadequate compared to what the expectations are.
The GP may have been riffing off of this "that's not AI" issue that goes way back.
The people who go around saying "LLMs aren't intelligent" while refusing to define exactly what they mean by intelligence (and hence not making a meaningful/testable claim) add nothing to the conversation.
I'll happily say that LLMs aren't intelligent, and I'll give you a testable version of it.
An LLM cannot be placed in a simulated universe, with an internally consistent physics system of which it knows nothing, and go from its initial state to a world-spanning civilization that understands and exploits a significant amount of the physics available to it.
I know that is true because if you place an LLM in such a universe, it's just a gigantic matrix of numbers that doesn't do anything. It's no more or less intelligent than the number 3 I just wrote on a piece of paper.
You can go further than that and provide the LLM with the ability to request sensory input from its universe and it's still not intelligent because it won't do that, it will just be a gigantic matrix of numbers that doesn't do anything.
To make it do anything in that universe you would have to provide it with intrinsic motivations and a continuous run loop, but that's not really enough because it's still a static system.
To really bootstrap it into intelligence you'd need to have it start with a very basic set of motivations that it's allowed to modify, and show that it can take that starting condition and grow beyond them.
You will almost immediately run into the problem that LLMs can't learn beyond their context window, because they're not intelligent. Every time they run a "thought" they have to be reminded of every piece of information they previously read/wrote since their training data was fixed in a matrix.
I don't mean to downplay the incredible human achievement of reaching a point in computing where we can take the sum total of human knowledge and process it into a set of probabilities that can regurgitate the most likely response to a given input, but it's not intelligence. Us going from flint tools to semiconductors, vaccines and spaceships, is intelligence. The current architectures of LLMs are fundamentally incapable of that sort of thing. They're a useful substitute for intelligence in a growing number of situations, but they don't fundamentally solve problems, they just produce whatever their matrix determines is the most probable response to a given input.
OK, but the people who go around saying "LLMs are intelligent" are in the same boat...
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